无人机三维路径规划的粒子群混合算法

路径规划是无人机控制过程中的重要环节之一,现有基于粒子群等算法的传统路径规划方法存在容易陷入局部最优等问题,无法适应现实场景中复杂环境及高搜索速度的要求。针对已有方法的缺陷,提出了一种无人机路径规划的高性能细菌觅食-遗传-粒子群混合算法,以传统粒子群优化算法为基础,引入细菌觅食算法及遗传算法思想,提高算法计算速度与能力,同时考虑实际场景中无人机的运行约束,进一步提高了方法的可用性。最后,利用仿真实验验证了所提方法的有效性,并通过与传统方法对比证明了所提方法在运行时间、规划航程等方面的优越性。     

基于自动模式匹配的数据恢复方法

To solve the problem of data recovery on free disk sectors, an approach of data recovering based on intelligent pattern matching is proposed in this paper. Different from the methods based on the file directory, this approach utilizes the consistency among the data on the disk. A feature pattern library is established based on different types of files according to the internal constructions of text. Data on sectors will be classified automatically by data clustering and evaluating. When the conflict happens on data classification, the digestion will be initiated by adopting context pattern. Based on this approach, the paper achieved the data recovery system aiming at pattern matching of txt, word and PDF files. Raw and formatting recovery tests proved that the system works well.